scholarly journals Multivariate Drought Frequency Analysis using Four-Variate Symmetric and Asymmetric Archimedean Copula Functions

2018 ◽  
Vol 33 (1) ◽  
pp. 103-127 ◽  
Author(s):  
Olusola O. Ayantobo ◽  
Yi Li ◽  
Songbai Song
2020 ◽  
Author(s):  
Hyung Jin Shin ◽  
Jong Won Do ◽  
Jae Nam Lee ◽  
Gyumin Lee ◽  
Mun Sung Kang

<p><span>According to the Korea Meteorological Administration, in 2018, Korea's national average temperature and maximum temperature are the highest in 111 years since meteorological observations (1907.10.1.) The highest value was observed since August 1 at </span><span> 39.6 </span>℃ <span>in Seoul. Heatwaves represent the number of days with the highest daily temperature above 33 ° C. The number of heatwaves in 18 years totaled 31.5 days. Heatwaves have a particularly significant effect on the growth and death of field crops. Indeed, 18,254 ha of field crops occurred nationwide. Precipitation in 2018 is higher than normal, but precipitation shortages have occurred due to seasonal and regional variations and local droughts due to the lowest precipitation from mid-July to late August. In particular, there were more rains than normal years at the beginning of farming season (March-May) and the end of farming season (October), but the summer agricultural drought occurred due to less precipitation than the average year-end of July-August. The second shortest rainy season (half of the average year) since 1987 and the rainy season was 72% compared to the average year, some of the reservoirs have caused a serious and severe stage. The country recorded the maximum number of rainfall days on 27th during the period of 7.10 ~ 8.5 days and 43 days on Chungnam. This is believed to have affected the drought occurrence by overlapping with the stage of water-forming, which requires the largest amount of water supply for rice growth. In the case of field crops, irrigation facilities are inferior to paddy fields, so field crop growth is directly related to no rainfall days, and droughts such as deterioration of field crops were recorded nationwide during the maximum rainfall period. Since the end of the rainy season, there have been a total of 22,767 ha droughts, iincluding 2,513 ha of paddy field and 20,254 ha of field crops, due to severe shortages of precipitation and damage to crops caused by heat waves. </span><span>For the 2018 rainfall-based drought frequency analysis, the analysis was based on cumulative precipitation from January to August of 18, and there was a severe shortage of precipitation from mid-July to mid-August, but the cumulative precipitation from January to August is normal. As a result of rainfall-based drought frequency analysis, the drought frequency area was analyzed into two regions for more than 10 years. Based on rainfall in July 2018, drought occurred in most parts of the country due to severe rainfall shortages. For over 200 years, the frequency of drought has been analyzed to 107 counties. As a result of the drought frequency analysis based on the reservoir storage rate in August 2018, there were 45 counties in the drought frequency area for more than 200 years due to the lack of water during the high demand period of rice crop growth period.</span></p><div data-hjsonver="1.0" data-jsonlen="11062"><span>This research was supported by a grant(2019-MOIS31-010) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety(MOIS).</span></div>


2021 ◽  
Author(s):  
Mohamad Haytham Klaho ◽  
Hamid R. Safavi ◽  
Mohamad H. Golmohammadi ◽  
Maamoun Alkntar

Abstract Historically, severe floods have caused great human and financial losses. Therefore, the flood frequency analysis based on the flood multiple variables including flood peak, volume and duration poses more motivation for hydrologists to study. In this paper, the bivariate and trivariate flood frequency analysis and modeling using Archimedean copula functions is focused. For this purpose, the annual flood data over a 55-year historical period recorded at the Dez Dam hydrometric station were used. The results showed that based on goodness of fit criteria, the Frank function built upon the couple of the flood peak-volume and the couple of the flood peak-duration as well as the Clayton function built upon the flood volume-duration were identified to be the best copula families to be adopted. The trivariate analysis was conducted and the Clayton family was chosen as the best copula function. Thereafter, the common and conditional cumulative probability distribution functions were built and analyzed to determine the periodic "and", "or" and "conditional" bivariate and trivariate flood return periods. The results suggest that the bivariate conditional return period obtained for short-term periods is more reliable than the trivariate conditional return period. Additionally, the trivariate conditional return period calculated for long-term periods is more reliable than the bivariate conditional return period.


2011 ◽  
Vol 32 (6) ◽  
pp. 831-842 ◽  
Author(s):  
M. Hallack-Alegria ◽  
J. Ramirez-Hernandez ◽  
D. W. Watkins

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